During combat, measuring the dimensions of targets is extremely important for knowing when to fire on the enemy. The importance of identifying a known target on land emphasizes the importance of techniques devoted to automatic target recognition. Although a number of object-recognition techniques have been developed in the past, none of them have provided the desired specifics for unidentified target recognition. Studies on target recognition are largely based on images that assume that images of a known target can be readily viewed under any circumstance. But this is not true for military operations conducted on various terrains under specific circumstances. Usually it is not possible to capture images of unidentified objects because of weather, inadequate equipment, or concealment. In this study, a new approach that integrates neural networks and laser radar has been developed for automatic target recognition in order to reduce the abovementioned problems. Unlike current studies, the proposed model uses the geometric dimensions of unidentified targets in order to detect and recognise them under severe weather conditions.
OPSOMMINGDie bepaling van teikenafmetings is van besondere belanggedurende gevegte sodat vuurtydstipte sodoende vasgelê kan word. In hierdie opsig word outomatiese uitkenning van teikentipe dus ook belangrik. Laasgenoemde tegnieke het desnieteenstaande nie besonder presteer met die uitkenning van vreemdeteikentipes nie. Terreintoestande, weersomstandighede, swak waarnemingstoerusting en kamoeflering speel in die verband ook 'n rol. Nuwerwetse toerusting wat gebruikmaak van neurale netwerke laserradar word voorgehou as 'n oplossing vir die vraagstuk onder uiteenlopende omgewingstoestande.